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Computing possible futures : model-based explorations of "what if?"

Author: William B Rouse
Publisher: Oxford ; New York, NY : Oxford University Press, [2019] ©2019
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
This book discusses the use of models and interactive visualizations to explore designs of systems and policies in determining whether such designs would be effective. Executives and senior managers are very interested in what "data analytics" can do for them and, quite recently, what the prospects are for artificial intelligence and machine learning. They want to understand and then invest wisely. They are  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
(OCoLC)1091587578
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: William B Rouse
ISBN: 9780192585431 0192585436 9780191881589 0191881589 9780192585448 0192585444
OCLC Number: 1119611780
Description: 1 online resource (202 pages)
Responsibility: William B. Rouse.

Abstract:

This book discusses the use of models and interactive visualizations to explore designs of systems and policies in determining whether such designs would be effective. Executives and senior managers are very interested in what "data analytics" can do for them and, quite recently, what the prospects are for artificial intelligence and machine learning. They want to understand and then invest wisely. They are reasonably skeptical, having experienced overselling and under-delivery. They ask about reasonable and realistic expectations. Their concern is with the futurity of decisions they are currently entertaining. They cannot fully address this concern empirically. Thus, they need some way to make predictions. The problem is that one rarely can predict exactly what will happen, only what might happen. To overcome this limitation, executives can be provided predictions of possible futures and the conditions under which each scenario is likely to emerge. Models can help them to understand these possible futures. Most executives find such candor refreshing, perhaps even liberating. Their job becomes one of imagining and designing a portfolio of possible futures, assisted by interactive computational models. Understanding and managing uncertainty is central to their job. Indeed, doing this better than competitors is a hallmark of success. This book is intended to help them understand what fundamentally needs to be done, why it needs to be done, and how to do it. The hope is that readers will discuss this book and develop a "shared mental model" of computational modeling in the process, which will greatly enhance their chances of success.

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